Resource management system, integrated resource management apparatus, and resource management method

Abstract

To provide a resource management system, an integrated resource management apparatus, and a resource management method for planning the use of shared resources at a plurality of locations while optimizing an overall KPI (Key Performance Indicator).SOLUTION: A resource management process by the resource management system solves an optimization problem in which the amount of change in KPI for each subsystem is a constraint condition and the amount of additional resource allocation (Δ resource) is an objective function, so that, when resources are reallocated based on the additional allocation amount, an additional allocation amount in a subsystem that improves KPIs compared with a resource initial allocation plan is calculated. If the KPIs actually achieved by each of the plurality of subsystems do not deteriorate after the resource reallocation, the acceptability of the acceptance is determined for each subsystem, and the acceptability of the resource reallocation plan is determined based on the acceptability of each of the plurality of subsystems.SELECTED DRAWING: Figure 3B

Description

[Technical field]

[0001] The present invention relates to a resource management system, an integrated resource management device, and a resource management method. [Background technology]

[0002] For example, Patent Document 1 discloses a power transmission control method, a power transmission management system, and a program that aim to "control the amount of electricity generated by a private power generation facility according to the demand of consumers who use a power interchange service, and transmit the generated electricity to the corresponding consumers via the power grid."

[0003] Specifically, the conventional technology disclosed in Patent Document 1 is configured as "a power transmission control method executed on a terminal connected to a communication network, comprising a process for individually predicting the amount of electricity that each consumer using a power interchange service will receive from the power grid, and a process for controlling the amount of electricity generated by each consumer's private power generation equipment and transmitted to the power grid in accordance with the predicted amount of electricity, and when the private power generation equipment is shared by multiple consumers using the power interchange service, the amount of electricity generated by the private power generation equipment is controlled within a range that satisfies a distribution ratio of each consumer predetermined among the multiple consumers, and the distribution ratio is changed in a predetermined time unit." [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 7202928 Summary of the Invention [Problem to be solved by the invention]

[0005] Here, we consider the case where the consumer is a fleet operator that operates multiple vehicles including EVs (Electric Vehicles). Each base of the fleet operator is equipped with facilities for charging EVs, and surplus electricity at each base can be shared between the bases as a shared resource according to a wheeling allocation plan.

[0006] In such cases, there is a need to develop vehicle operation plans and transportation allocation plans for multiple bases of a fleet operator while optimizing the overall KPI, which is the sum of the KPIs (Key Performance Indicators) of each base.

[0007] However, in the above-mentioned conventional technology, the distribution ratio is determined based on the power demand of each consumer as a given condition, so there is a problem that it is not possible to consider the optimization of the overall KPI, which changes depending on the increase or decrease in the power demand of each consumer. This problem is not limited to vehicle operation plans that allocate surplus power at each base as a shared resource, but also applies to cases where a utilization plan for shared resources at multiple bases is planned while taking into account the overall KPI.

[0008] The present invention has been made in consideration of the above circumstances, and has an object to make it possible to formulate a utilization plan for shared resources at multiple locations while optimizing overall KPIs. [Means for solving the problem]

[0009] As one aspect for solving the above-mentioned problem, there is provided a resource management system including a plurality of subsystems, and calculating a resource allocation plan for allocating resources to the plurality of subsystems, the resource management system having a processor and a memory, the processor of the resource management system calculating an initial resource allocation plan for implementing an initial allocation of resources to the plurality of subsystems, and calculating a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is implemented based on the initial resource allocation plan. the resource reallocation plan for reallocating resources to the plurality of subsystems based on the additional allocation amount and an estimated value of the KPI that is estimated to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; the resource reallocation plan for reallocating resources to the plurality of subsystems based on the additional allocation amount and an estimated value of the KPI that is estimated to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; the resource reallocation plan for calculating the KPI that is estimated to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; the resource reallocation plan for calculating the KPI that is estimated to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; the resource reallocation plan for calculating the KPI that is estimated to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; Effect of the Invention

[0010] According to the present invention, it is possible to formulate a utilization plan for shared resources among a plurality of bases while optimizing the overall KPI. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is an explanatory diagram of an overview of a resource management system according to a first embodiment. [Diagram 2]FIG. 1 is a diagram showing an example of the configuration of a resource management system according to a first embodiment. [Figure 3A] 6 is a flowchart showing an example of a resource management process according to the first embodiment. [Figure 3B] 6 is a flowchart showing an example of a resource management process according to the first embodiment. [Figure 3C] 6 is a flowchart showing an example of a resource management process according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of the configuration of consignment allocation time series data according to the first embodiment. [Diagram 5] FIG. 4 is a diagram showing an example of the configuration of resource addition proposal data according to the first embodiment. [Figure 6A] 4 is a diagram showing an example of the configuration of an estimated ΔKPI value, a calculated ΔKPI value, and acceptance / rejection data (successful case) according to the first embodiment. FIG. [Figure 6B] 4 is a diagram showing an example of the configuration of an estimated ΔKPI value, a calculated ΔKPI value, and acceptance / rejection data (case of rejection) according to the first embodiment. FIG. [Figure 7] FIG. 4 is a diagram showing an example of a display of a resource allocation negotiation process according to the first embodiment. [Figure 8] FIG. 2 is a diagram showing an example of calculation (subsystem 1 (proposer)) of a resource allocation negotiation process according to the first embodiment. [Figure 9] FIG. 2 is a diagram showing an example of calculation (subsystem 2 (decision side)) of a resource allocation negotiation process according to the first embodiment. [Figure 10] 11 is a flowchart showing a detailed example of a Δ resource calculation process by interchanging an objective function and a constraint condition according to the first embodiment. [Figure 11] FIG. 4 is an explanatory diagram of a modified example of the first embodiment. [Figure 12] 11 is a flowchart showing an example of a resource management process (planning phase: resource allocation negotiation process) according to the second embodiment. [Figure 13A] FIG. 13 is a diagram showing an example of the configuration of ΣΔKPI (achieved case) according to the second embodiment. [Figure 13B] FIG. 13 is a diagram showing an example of the configuration of ΣΔKPI (failed case) according to the second embodiment. [Figure 14] FIG. 13 is a diagram showing an example of a ΔKPI / Δresource map according to the third embodiment. [Figure 15] FIG. 13 is a diagram showing an example of a dataset of Δ resources·Δ KPI according to the third embodiment. [Figure 16] 11 is a flowchart showing an example of an energy management process (planning phase: initial planning process) according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that the embodiments described below do not limit the invention according to the claims, and all of the elements and combinations thereof described in the embodiments are not necessarily essential to the solution of the invention.

[0013] In the following description, a program realizing each processing function unit is executed by a processor to perform a predetermined process using a storage resource (e.g., a memory) and / or a communication interface device (e.g., a port) as appropriate. The processor is, for example, a CPU (Central Processing Unit). Therefore, the process executed by each processing function unit may be a process performed by a processor or a computer having the processor.

[0014] In the following description, identical or similar components are given the same reference numerals, and in the following embodiments and examples, the description may be omitted or only the differences may be described. In addition, when there are multiple identical or similar components, they may be described with different subscripts added to the same reference numerals. In addition, when it is not necessary to distinguish between these multiple components, the subscripts may be omitted. The number of each component may be singular or plural unless otherwise specified.

[0015] In the following explanation, various information is expressed in table format, but the information is not limited to table format and may be in CSV (Comma Separated Values) or other formats. Since various information does not depend on the data format, for example, "XXX table" can be called "XXX information".

[0016] In addition, among the items in the various information, the names of items that include information in the item name to distinguish the corresponding record from other records, such as "# (number)", "identification information", "ID", and "name", may be interchangeable.

[0017] [Embodiment 1] 1 is an explanatory diagram of an overview of a resource management system S according to a first embodiment. In this embodiment, the resource management system S is described as a multi-site fleet energy management system having one power transmission site that transmits surplus power from its own site and two power receiving sites that receive surplus power from other sites. The power transmission site is equipped with a large-capacity distributed power source, and transmits excess power over the power demand for buildings and EV charging at its own site to the power receiving site as surplus power, which is a shared resource.

[0018] Each of the power transmission and receiving points is a charging station (vehicle depot, logistics center, bus terminal, etc.) for multiple EVs (Electric Vehicles) of a fleet operator (bus operator, truck operator, etc.) that operates multiple vehicles. The fleet operator may be a single operator or multiple operators in a cooperative relationship.

[0019] Each base is equipped with distributed power sources (PV (PhotoVoltaic, solar power generation equipment), fuel cells, engine generators including hydrogen co-firing, etc.), and surplus electricity (power generation exceeding demand) at each base is shared as a shared resource (sometimes simply called resource). For example, in Japan, under the self-dispatch system, surplus electricity can be shared by using the transmission and distribution lines of the electricity transmission and distribution company.

[0020] In this embodiment, the vehicle operation mode is route delivery and route bus (trucks and buses are dispatched on a fixed circular route), but the operation mode and vehicle type are not limited. The vehicles may be only EVs, or a mixture of EVs and internal combustion engine vehicles (ICE (Internal Combustion Engine)). The difference in performance (cruising range and transport capacity) between EVs and ICEs or between EVs provides the degree of freedom in vehicle dispatch. KPIs (Key Performance Indicators) such as CO2 emissions and energy costs change depending on the frequency of charging opportunities and the power supply configuration of the power supply.

[0021] The EMS (Energy Management System) at each site is a set of independent subsystems (loosely coupled systems) that individually create power supply and demand plans (power generation, charging and discharging of stationary batteries, and EV charging). The EMS at each site may be a system that includes the FMS (tightly coupled system), or a system independent of the FMS. In this embodiment, the EMS and FMS are tightly coupled systems that simultaneously create power supply and demand plans and vehicle operation plans for each site.

[0022] The multiple base EMS2, which are subsystems loosely coupled via a network, are provided for each of the power transmission and receiving bases and have the functionality of an Fleet Management System (FMS).The base EMS2 simultaneously creates power supply and demand plans (plans for power generation, stationary battery charging and discharging, and EV charging) and vehicle operation plans (dispatch of vehicles to designated routes) for its own base.

[0023] In this embodiment, the resource management system S includes a multi-site integrated EMS (integrated resource management device) 1 and multiple site EMSs 2. However, the distribution of the functions of the multi-site integrated EMS 1 and the multiple site EMSs 2 is not limited to this embodiment described below. In other words, the processing performed by the multi-site integrated EMS 1 may be executed by one or multiple site EMSs 2, and the processing performed by one or multiple site EMSs 2 may be executed by the multi-site integrated EMS 1.

[0024] The multi-site integrated EMS1, which has an allocation function, manages the resource allocation negotiation process between the base EMS2 of multiple power receiving bases based on resource sharing information (time series data on surplus power) from the base EMS2 of the power transmission base, and develops a transmission allocation plan (resource allocation plan).

[0025] First, in step S1, the base EMS 2 of the power transmission base transmits information on surplus power at its own base as resource sharing information to the multi-base integration EMS 1. Next, in step S2, the multi-base integration EMS 1 calculates a resource allocation plan based on the resource sharing information received from the base EMS 2 of the power transmission base (initial calculation).

[0026] Next, in step S3, the multi-site integrated EMS 1 transmits the resource allocation plan calculated in step S2 to the site EMSs 2 of the power receiving sites 1 and 2.

[0027] Next, in step S4, the base EMS 2 of power receiving bases 1 and 2 initially calculate a resource usage plan based on the resource allocation plan transmitted in step S3. If the base EMS 2 of power receiving base 1 is expected to improve its own base's individual KPI by adding resources based on the resource allocation plan, it calculates it as resource addition proposal data D102 (described below) including Δresources (amount of resource addition) and ΔKPI (amount of KPI improvement). Δresources (amount of resource addition) and ΔKPI (amount of KPI improvement) are called negotiation parameters. ΔKPI is a value obtained by subtracting the KPI after the resources are added from the KPI before the resources are added.

[0028] In step S5, the site EMS 2 of the power receiving site 1 transmits the negotiation parameters calculated in step S4 to the multi-site integrated EMS 1. Note that the site EMS 2 of the power receiving site 2 does not calculate negotiation parameters and does not transmit them to the multi-site integrated EMS 1 because it has determined that the individual KPIs of its own site cannot be improved by adding resources based on the resource allocation plan transmitted in step S3.

[0029] Next, in step S6, the multi-site integrated EMS 1 recalculates the resource allocation plan based on the resource addition proposal (negotiation index) received from the site EMS 2 of the power receiving site 1. Next, in step S7, the multi-site integrated EMS 1 transmits the resource allocation plan together with a response request to the site EMS 2 of the power receiving sites 1 and 2.

[0030] Next, in step S8, the base EMS2 of the power receiving bases 1 and 2 recalculates the resource usage plan based on the resource allocation plan transmitted in step S7, and determines whether to accept or reject the resource allocation plan. Next, in step S9, the base EMS2 of the power receiving bases 1 and 2 responds to the multi-base integrated EMS1 with the acceptance or rejection determined in step S8.

[0031] The multi-site integrated EMS 1 aggregates the responses from the site EMS 2 of the power receiving sites 1 and 2, evaluates the overall KPI, and if improvement is expected, adopts the resource allocation plan calculated in step S6. The multi-site integrated EMS 1 notifies the site EMS 2 of the power receiving sites 1 and 2 of the adoption of the resource allocation plan.

[0032] (Configuration of resource management system S according to embodiment 1) 2 is a diagram showing an example of the configuration of a resource management system S according to embodiment 1. The resource management system S includes a multi-site integration EMS 1 and a plurality of site EMSs 2.

[0033] The multi-site integrated EMS 1 has a communication device 11, a calculation device 12, a storage device 13, and an input / output device 14. The communication device 11 is a communication interface that enables the multi-site integrated EMS 1 to communicate with the site EMSs 2 via a public network or a closed network, whether wired or wireless. The calculation device 12 is a processor represented by a CPU (Central Processing Unit). The storage device 13 includes memory and storage. The input / output device 14 includes input devices such as a keyboard and a mouse, and output devices such as a display.

[0034] The calculation device 12 executes a program in cooperation with the memory to realize a resource allocation planning unit 121 and a response aggregating unit 122. The calculation device 12 also executes a program in cooperation with the memory to realize a ΔKPI·Δ resource map display function unit 141 as an output function on the input / output device 14.

[0035] The storage device 13 stores the surplus power time-series data 131 as well as various programs and various data.

[0036] The base EMS 2 has a communication device 21, a calculation device 22, a storage device 23, and an input / output device 24. The communication device 21 is a communication interface that enables the base EMS 2 to communicate with the multi-base integrated EMS 1 via a public network or a closed network, whether wired or wireless. The calculation device 22 is a processor such as a CPU. The storage device 23 includes memory and storage. The input / output device 24 includes input devices such as a keyboard and a mouse, and output devices such as a display.

[0037] The arithmetic device 22 executes the program in cooperation with the memory to realize a resource usage planning unit 221, a Δ resource calculation unit 222, and a Δ KPI evaluation and response unit 223. The arithmetic device 22 also executes the program in cooperation with the memory to realize a vehicle operation and power supply and demand plan display function unit 241 on the input / output device 24.

[0038] The storage device 23 stores plan condition data 231, vehicle operation data 232, and power supply and demand data 233, as well as various programs and various data.

[0039] The plan condition data 231 includes equipment information, operation conditions, and supply and demand conditions. The equipment information includes EV vehicle specifications, distributed power source specifications, and stationary battery (BESS (Battery Energy Storage System)) specifications. The operation conditions include the route configuration on which vehicles including EVs operate, EV power consumption, and power and fuel unit prices. The supply and demand conditions include a building power demand forecast, and a solar power generation forecast.

[0040] The vehicle operation data 232 is a vehicle operation plan (dispatch of vehicles to routes) calculated by the resource utilization plan unit 221.

[0041] The power supply and demand data 233 is a power supply and demand plan (including EV charging, charging and discharging of stationary batteries, power generation, and photovoltaic power generation output suppression) calculated by the resource utilization planning unit 221.

[0042] The multi-site integrated EMS 1 and the site EMS 2 transmit and receive information by performing network communication via communication devices 11 and 21. The multi-site integrated EMS 1 may be either an on-premise system or a cloud-based system.

[0043] The base EMS 2 may be an add-in system to the fleet management system that creates a vehicle operation plan for each fleet operator. Alternatively, the base EMS 2 may be a system that includes the fleet management system of each fleet operator or is included in the fleet management system. Alternatively, the base EMS 2 may be a cloud system that cooperates with the fleet management system of each fleet operator.

[0044] (Resource Management Process According to the First Embodiment) 3A, 3B, and 3C are flowcharts illustrating an example of a resource management process according to the first embodiment.

[0045] In FIG. 3A to FIG. 3C, the functions of the base EMS (subsystem 1) 2-1 and the base EMS (subsystem 1) 2-2 are equivalent. The base EMS (subsystem 1) 2-1 is the proposal side, and the base EMS (subsystem 1) 2-2 is the decision side. The wheeling allocation time series data D101 is data that is increased or decreased by multiplying the surplus power time series data (not shown) by a predetermined coefficient. In other words, the negotiation parameter is a scalar value. The surplus power time series data may be increased or decreased for each time frame of the time series, but the negotiation parameter becomes vectorized and becomes huge. In addition, the time change of the self wheeling is absorbed by a fixed battery installed at the own base. For this reason, the wheeling allocation time series data D101 is increased or decreased by calculating a predetermined coefficient for each predetermined unit time, such as a day, and multiplying it by the surplus power time series data.

[0046] Steps S11 to S15 in FIG. 3A show the resource management processing (planning phase: initial planning process).

[0047] First, in step S11, the multi-site integrated EMS 1 receives surplus power time series data from the base EMS 2 of the power transmission base, and updates the resource sharing information. Next, in step S12, the resource allocation planning unit 121 of the multi-site integrated EMS 1 calculates an initial resource allocation plan, i.e., an initial wheeling allocation plan. In the initial calculation of the wheeling allocation plan, the multi-site integrated EMS 1 evenly allocates the surplus power time series data to the target bases for each date and time. The initial wheeling allocation plan is as exemplified in the wheeling allocation time series data D101 (before negotiation (table on the left side of FIG. 4)).

[0048] In the resource allocation plan shown in Fig. 4, solar power generation is assumed as the surplus power source, so surplus power occurs during the daytime. Therefore, before the resource allocation negotiation shown in the table on the left of Fig. 4, resources are equally distributed between the EMSs 2-1 and 2-2 at each site.

[0049] Next, in step S13, the resource allocation planning unit 121 of the multi-site integrated EMS 1 transmits to the site EMSs 2-1 and 2-2 the pre-negotiation consignment allocation time series data D101 corresponding to the initial consignment allocation plan (initial resource allocation plan) initially calculated in step S12.

[0050] Next, in step S14, the resource usage planning unit 221 of the base EMS 2-1, 2-2 calculates a usage plan for the shared resources at the base and an individual KPI for the base based on the wheeling allocation time series data D101 transmitted in step S13 from the multi-base integrated EMS 1. The resource usage planning unit 221 of the base EMS 2-1, 2-2 calculates, for example, a vehicle operation and power supply and demand plan as the usage plan for the shared resources, and calculates the amount of CO2 emissions as the individual KPI for the base.

[0051] Next, in step S15, the resource usage planning unit 221 of the base EMS 2-1, 2-2 determines whether the individual KPI of the base calculated in step S14 will improve by using the shared resource. If the individual KPI of the base is improved, the resource usage planning unit 221 adopts the shared resource usage plan calculated in step S14. In step S15, if the individual KPI of the base is not improved, the base EMS 2-1, 2-2 rejects the shared resource usage plan calculated in step S14.

[0052] Steps S16 to S28 in Fig. 3B show resource management processing (planning phase: resource allocation negotiation process). In the resource allocation negotiation process shown in Fig. 3B, the base EMS 2-1 transmits a request for adding shared resources to the multi-base integrated EMS 1, assuming that the additional shared resources will further improve the individual KPIs of the base. Note that only the base EMS 2-1 may transmit a request for adding shared resources to the multi-base integrated EMS 1, or both the base EMSs 2-1 and 2-2 may transmit a request for adding shared resources to the multi-base integrated EMS 1.

[0053] Next, in step S16, the Δresource calculation unit 222 of the base EMS 2-1 calculates Δresources if the individual KPI of the base calculated in step S14 does not improve by using the shared resources. Δresources can be calculated by solving an optimization problem with the change amount ΔKPI (CO2 reduction amount) as a constraint condition and Δresources (additional amount of wheeling allocation or additional allocation amount) as an objective function. A positive value of ΔKPI indicates an improvement in the KPI, and a negative value indicates a deterioration in the KPI. A positive value of Δresources indicates an addition of wheeling allocation, and a negative value indicates a reduction in wheeling allocation.

[0054] Next, in step S17, the Δ resource calculation unit 222 of the base EMS 2-1 judges whether the ΔKPI calculated in step S16 has improved (is a positive value). If the ΔKPI has improved, the Δ resource calculation unit 222 generates resource addition proposal data D102 (FIG. 5) including the Δ resource corresponding to this ΔKPI. The resource addition proposal data D102 corresponds to each row identified by the ID in FIG. 5.

[0055] The resource addition proposal data D102 shown in Fig. 5 is data for each base EMS2-1 of the proposal side. The resource addition proposal data D102 is described as a surcharge rate for the consignment allocation time series data D101. For example, when Δresource is "+0.5", a resource allocation of 1.5 times (1+0.5) is proposed for the consignment allocation time series data D101 of the resource allocation plan.

[0056] Next, in step S18, the Δ resource calculation unit 222 of the base EMS 2-1 transmits the resource addition proposal data D102 generated in step S17 to the multi-base integrated EMS 1.

[0057] Next, in step S19, the resource allocation planning unit 121 of the multi-site integrated EMS 1 recalculates the resource allocation plan (resource reallocation plan) and the expected value of ΔKPI (i.e., the consignment allocation plan and the expected value of the CO2 increase). The resource allocation planning unit 121 of the multi-site integrated EMS 1 recalculates the resource allocation plan (resource reallocation plan) and the expected value of ΔKPI based on the resource addition proposal data D102 transmitted from the base EMS 2-1 in step S18. The recalculated resource allocation plan inherits the ID of the resource addition proposal data D102 received from the base EMS 2-1. The resource allocation plan recalculated in step S20 is as exemplified in the consignment allocation time series data D101 (after negotiation (the table on the right side of FIG. 4)).

[0058] After the resource allocation negotiation shown in the table on the right side of FIG. 4, the resource allocation between base EMS 2-1 and base EMS 2-2 has changed to 1.5:0.5, compared to the case in which the resource allocation before the negotiation was equal.

[0059] Next, in step S20, the multi-site integrated EMS 1 transmits an acceptance / rejection inquiry including the resource allocation plan and the ΔKPI expected value recalculated in step S19 to the site EMSs 2-1 and 2-2. Here, in the case where there are two subsystems as in this embodiment, the negative value of the Δ resource of the proposing subsystem is set as the positive Δ resource of the determining subsystem. Also, in the case where there are three or more subsystems, the negative value of the Δ resource of the proposing subsystem is prorated by the number of sites of the determining subsystem and set as the positive Δ resource of the determining subsystem. Similarly, the negative value of the ΔKPI of the proposing subsystem is prorated by the number of sites of the determining subsystem and set as the ΔKPI expected value of the determining subsystem.

[0060] Next, in step S21, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 recalculates the shared resource utilization plan at the base based on the resource allocation plan transmitted from the multi-base integrated EMS 1 in step S20.

[0061] Next, in step S22, the ΔKPI evaluation and response unit 223 of the base EMS2-2 recalculates the variation ΔKPI for the individual KPI of its own base initially calculated in step S14, based on the shared resource usage plan recalculated in step S21.

[0062] Next, in step S23, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 compares the ΔKPI (ΔKPI calculated value) calculated in step S22 with the ΔKPI expected value transmitted from the multi-base integrated EMS 1 in step S20. Then, if the ΔKPI calculated value≦ΔKPI expected value, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 accepts the resource allocation plan transmitted from the multi-base integrated EMS 1 in step S20. On the other hand, if the ΔKPI calculated value>ΔKPI expected value, the ΔKPI evaluation and response unit 223 rejects the resource allocation plan transmitted from the multi-base integrated EMS 1 in step S20, determining whether to accept the resource allocation plan.

[0063] On the other hand, in step S24, the ΔKPI evaluation and response unit 223 of the base EMS 2-1 decides to accept the resource allocation plan sent from the multi-base integrated EMS 1 in step S20 because the resource allocation plan is based on the shared resource addition proposal made by its own device.

[0064] Next, in step S25, the resource utilization planner 221 of the base EMS 2-2 transmits a response to the multi-base integrated EMS 1 as to whether or not to accept the resource allocation plan determined in step S23 or S24.

[0065] Next, in step S26, the resource allocation planning unit 121 of the multi-site integrated EMS 1 determines whether to adopt the resource allocation plan recalculated in step S19 when it receives responses of acceptance of the resource allocation plan from all the base EMSs 2 that are subsystems. If there is even one base EMS 2 that has sent a rejection response, the resource allocation planning unit 121 of the multi-site integrated EMS 1 determines whether to reject the resource allocation plan recalculated in step S19.

[0066] The resource management process (planning phase: resource allocation negotiation process) in steps S16 to S28 in Fig. 3B may be repeatedly executed until the resource allocation plan is minimized in step S26. Alternatively, if the number of times the resource management process (planning phase: resource allocation negotiation process) is repeatedly executed reaches an upper limit, the resource allocation plan initially calculated in step S12 (Fig. 3A) may be adopted.

[0067] 6A and 6B show an example of a determination result of the multi-site integrated EMS 1 in step S26 based on the responses transmitted from both the site EMSs 2-1 and 2-2 to the multi-site integrated EMS 1 in step S25.

[0068] In Figure 6A, the acceptance of the resource allocation plan with "ID" "Plan0001" at all base EMS2-1, 2-2 is "accepted", and the total of the ΔKPI calculated value (CO2 emissions) across base EMS2-1, 2-2 is "-20". Since the ΔKPI calculated value of "-20" is a better value than the ΔKPI assumed value of "0", the adoption of the resource allocation plan with "ID" "Plan0001" is "established".

[0069] Meanwhile, in Figure 6B, the acceptance / rejection of the resource allocation plan with "ID" "Plan0001" at base EMS2-1 is "accepted." Meanwhile, the acceptance / rejection of base EMS2-2 is "rejected," and the total of the ΔKPI calculated value (CO2 emissions) for bases EMS2-1 and 2-2 is "+20." Since the ΔKPI calculated value of "+20" is a worse value than the ΔKPI assumed value of "0," the adoption of the resource allocation plan with "ID" "Plan0001" is "not established."

[0070] Next, in step S27, the resource allocation planning unit 121 of the multi-site integrated EMS 1 transmits an adoption notice that the resource allocation plan was adopted in step S26 to all the site EMSs 2-1 and 2-2. Next, in step S28, the resource usage planning units 221 of the site EMSs 2-1 and 2-2 adopt the resource usage plan of the shared resources that was decided to be adopted in step S28. The resource usage plan adopted in step S28 is the resource usage plan after the resource allocation negotiation.

[0071] Step S29 in FIG. 3C shows the resource management process (execution phase).

[0072] In step S29, the base EMS 2-1, 2-2 implements the resource usage plan adopted in step S15 (FIG. 3A) or step S28 (FIG. 3B). Specifically, the base EMS 2-1, 2-2 implements vehicle operation, EV charging, charging and discharging of stationary batteries at its own base in accordance with the resource usage plan. The resource usage plan adopted in step S15 is the resource usage plan before the negotiation of resource allocation.

[0073] (Display of resource allocation negotiation process according to embodiment 1) 7 is a diagram showing an example of a display 141D of a resource allocation negotiation process according to embodiment 1. The ΔKPI·Δ resource map display function unit 141 of the multi-site integrated EMS 1 can visualize the resource allocation negotiation process for a user on a display screen via the display 141D as shown in FIG.

[0074] Referring to display 141D, after two rounds of resource allocation negotiations, the total CO2 emissions at base 1 corresponding to base EMS2-1 and base 2 corresponding to base EMS2-2 have clearly decreased, as can be seen from the graph on the left side of FIG. 7.

[0075] On the other hand, as can be seen from the graph on the right side of Fig. 7, the CO2 emissions at base 1 clearly decrease with an increase in self-dispatch, whereas the CO2 emissions at base 2 increase with a decrease in self-dispatch. Self-dispatch is the transmission of electricity generated by a company to its own facilities via the electricity transmission and distribution network. Arrows 141D1 and 141D2 in the graph on the right side of Fig. 7 indicate the progress of negotiations on resource allocation, such as the initial resource allocation, the resource allocation after the first negotiation, and the resource allocation after the second negotiation.

[0076] Referring to the graph on the right of Figure 7, it can be seen that for base 1, the increase in the slope of arrow 141D1 (ΔKPI / Δresources) is large, the amount of CO2 reduction is large relative to the increase in the wheeling allocation amount, and the utilization value of the shared resources is high. For base 2, the decrease in the slope of arrow 141D2 (ΔKPI / Δresources) is small, the amount of CO2 increase is small relative to the decrease in the wheeling allocation amount, and the utilization value of the shared resources is low. This suggests that the overall KPI will improve by base 1, which has high utilization value, using more shared resources, and it can be seen that this will be achieved through the resource allocation negotiation process.

[0077] By referring to the display 141D, the user can understand how the CO2 emissions change in accordance with an increase or decrease in the self-consignment volume of each base, and can recognize whether or not the reallocation of the shared resources is appropriate.

[0078] (Calculation of resource allocation negotiation process according to the first embodiment) 8 and 9 are diagrams showing an example of calculation of the resource allocation negotiation process according to embodiment 1. Fig. 8 shows calculation of the resource allocation negotiation process in the base EMS 2 of the subsystem 1 (proposal side). Fig. 9 shows calculation of the resource allocation negotiation process in the base EMS 2 of the subsystem 2 (decision side).

[0079] 8 and 9, at power receiving point 1 and power receiving point 2, solar power is used to charge the BESS during the day, from approximately 8:00 to 16:00, and is used to charge the EV during the night, from 16:00 to 8:00 the next day. In graphs (b11), (b12), (b21), and (b22) in Fig. 8, the positive part of the vertical axis represents power demand, and the negative part represents power supply.

[0080] At the power receiving point 1 of the subsystem 1 (proposal side) shown in Fig. 8, before negotiations on resource allocation, as shown in the graph (b11), there are restrictions on the contract power, and the amount of power charged by the BESS during the day is also small because there is little self-consignment during the day. Therefore, the amount of charge of EV1, EV2, and EV3 by BESS discharge at night is limited. For this reason, as shown in the graph (a11), EV1, EV2, and EV3 are assigned to deliveries on short-distance routes compared to the internal combustion engine vehicles ICE1, ICE2, and ICE3. ICE stands for Internal Combustion Engine.

[0081] On the other hand, after the resource allocation negotiation at the power receiving point 1 of the subsystem 1 (proposal side) shown in Fig. 8, as shown in the graph (b12), the amount of energy charged by the BESS during the day increases because self-delivery during the day is added (see arrow "1" in the graph (b12)). This increases the amount of energy discharged by the BESS during the night (see arrow "2" in the graph (b12)), which increases the amount of energy charged by EV1, EV2, and EV3 (see arrow "3" in the graph (b12)). For this reason, as shown in the graph (a12), EV1, EV2, and EV3 are changed to be allocated to delivery on long-distance routes compared to the internal combustion engine vehicles ICE1, ICE2, and ICE3.

[0082] On the other hand, at the power receiving point 2 of the subsystem 2 (decision side) shown in Fig. 9, before the negotiation of resource allocation, as shown in the graph (b21), the self-consignment during the day is sufficient, and the amount of power for the BESS charging during the day is sufficient. Therefore, the amount of power for charging EV1, EV2, and EV3 by the BESS discharging at night is sufficient. Therefore, as shown in the graph (a21), EV1, EV2, and EV3 are assigned to delivery on long-distance routes compared to the internal combustion engine vehicles ICE1, ICE2, and ICE3.

[0083] On the other hand, after the resource allocation negotiation at the power receiving point 2 of the subsystem 2 (decision side) shown in Fig. 9, the self-dispatch during the day decreases, but the amount of power for the BESS charging during the day is still sufficiently secured (see arrow "1" in graph (b22)). Therefore, the BESS discharge during the night is still sufficiently secured (see arrow "2" in graph (b22)), and therefore the amount of power for charging EV1, EV2, and EV3 is still sufficiently secured (see arrow "3" in graph (b22)). Therefore, as shown in graph (a22), even if the self-dispatch at the power receiving point 2 decreases, there is still no change in the dispatch of EV1, EV2, and EV3 so that they are assigned to deliveries on long-distance routes compared to the internal combustion engine vehicles ICE1, ICE2, and ICE3. However, the amount of retail power supply used during the night increases, so CO2 emissions increase.

[0084] (Details of ΔResource Calculation Process (Steps S16 to S18 (FIG. 3B))) Fig. 10 is a flowchart showing a detailed example of the Δ resource calculation process by interchanging the objective function and the constraint condition according to the embodiment 1. Fig. 10 is a flowchart showing in detail steps S16 to S18 shown in Fig. 3B. In this embodiment, the detailed processing of the Δ resource calculation process is executed by the base EMS 2-1, which is the proposing subsystem 1.

[0085] Prior to explaining the flowchart, the constraint conditions and objective functions of the vehicle operation plan and the power supply and demand plan will be explained. The constraint conditions and objective functions of the vehicle operation plan and the power supply and demand plan can be written and calculated in the same manner as, for example, the method described in Reference 1. Reference 1: "Vehicle allocation / charging plan to expand electrification coverage in route delivery with a mix of EV and diesel vehicles" (Masatoshi Kumagai et al., 2022 Electrical Engineering Society of Japan Power and Energy Division Conference)

[0086] In this embodiment, the application of the method described in Document 1 is expanded to include power generation by on-site PV (photovoltaic power generation equipment at a base), charging and discharging of stationary batteries, and self-wheeling.

[0087] In the following formulas, capital letters are constants (given conditions) and lowercase letters are variables (planning targets). In this embodiment, vehicles are not allowed to share routes between multiple bases, and vehicle operation plans are made for each base.

[0088] 1. Constraints (Vehicle Allocation) Let x(v,d,r) be a dispatch variable that represents the association between vehicle v and route r on date d (1: assigned, 0: not assigned), and the constraint for assigning vehicle v to any route r on date d is expressed by equation (1). Σ_r in equation (1) represents the sum over all routes r. Σr x(v,d,r) = 1 (1)

[0089] Furthermore, the constraint that one vehicle is assigned to route r on date d is expressed by equation (2). Σv x(v,d,r) = 1 (2)

[0090] Here, if A_travel(k,r) is a parameter matrix representing the travel distance along route r at time k, the constraint condition representing the travel distance z(v,t) of vehicle v at time t based on the dispatch variables is expressed by equation (3). z(v,t) = z(v,d,k) = Σ_r (x(v,d,r) A_travel(k,r))...(3)

[0091] Furthermore, with A_site(k,r) being a parameter matrix representing stay at a site on route r at time k (1: stay, 0: absence), and C being the charger output, the constraint representing the charge amount y(v,t) of vehicle v at time t based on vehicle dispatch (however, in the case of an ICE, this is always 0) is expressed by equation (4). y(v,t) = y(v,d,k) ≦ C Σ_r (x(v,d,r) A_site(k,r))...(4)

[0092] 2. Constraints (changes in vehicle battery storage capacity) If the electricity cost of an EV is M_ev(v) [km / kWh], the constraint condition that expresses the change in the amount of stored energy b(v,t) of vehicle v is expressed by equation (5). Equation (5) expresses that the amount of stored energy at time t is calculated by adding the amount of charge y(v,t) at time t to the amount of stored energy at time t-1, and subtracting the amount of power consumed while traveling z(v,t) / M_ev(v) at time t. b(v,t) = b(v,t-1) + y(v,t) - z(v,t) / M_ev(v) (5)

[0093] In addition, the constraint condition that limits the change in the amount of stored electricity due to charging and driving to between the lower limit Bmin(v) and upper limit Bmax(v) of the amount of stored electricity in vehicle v is expressed by equation (6). Bmin(v) ≦ b(v,t) ≦ Bmax(v) (6)

[0094] 3. Constraints (supply and demand balance at bases) The constraint condition (supply and demand balance at the base) is expressed by equation (7). W_bld(t) + w_bs,charge(t) + Σ_v y(v,t) = W_pv(t) + w_rt(t) + w_sc(t) + w_bs,discharge(t)...(7) Where: W_bld(t): Building electricity demand (given time series data) W_pv(t): On-site PV power generation (given time series data) w_bs,charge(t): Charge amount of the stationary battery (subject to exclusion constraints with respect to discharge amount and capacity constraints of the stationary battery) w_bs,discharge(t): Discharge amount of stationary battery w_rt(t): Retail supply (upper limit is limited by contracted power) w_sc(t): The amount of electricity received through self-consignment.

[0095] 4. Regarding the amount of electricity received by self-consignment The amount of power received by the self-consignment is expressed by equation (8). w_sc(t) = sW_pl(t) (8) Where: W_pl(t): Time series data of wheeling distribution: Surplus power distributed to this base in the wheeling distribution plan drawn up by the distribution function s: Wheeling distribution gain (when fixed at s = 1, surplus power is received and used according to the wheeling distribution plan).

[0096] 5. Objective function (minimizing CO2 emissions) The objective function (minimization of CO2 emissions) is expressed by equation (9). G_rt Σ_t w_rt(t) + G_sc Σ_t w_sc(t) + G_ice Σ_v,v ∈V_ice (Σ_t z(v,t) / M_ice(v))···(9) Where: G_rt is the CO2 emission coefficient for retail electricity supply [kg-CO2 / kWh], and G_sc is the CO2 emission coefficient for surplus electricity [kg-CO2 / kWh]. G_ice is the CO2 emission factor of the ICE fuel [kg-CO2 / L], M_ice(v) is the fuel efficiency of the ICE [km / L] The first term is the CO2 emissions from retail supply including buildings and EVs, the second term is the CO2 emissions from self-delivery, and the third term is the CO2 emissions from ICE.

[0097] Minimizing equation (9) minimizes the total CO2 emissions from buildings and vehicles (EV and ICE), and also minimizes the CO2 emissions from vehicles.

[0098] In addition, if an upper limit is set for the objective function in formula (9) and the wheeling allocation gain is made the target for minimization, that is, the objective function and the constraints are interchanged, the wheeling allocation amount required to keep the CO2 emissions below a certain level is calculated. If the CO2 emissions and wheeling allocation amount are expressed as differences, they become ΔKPI (CO2 reduction amount) and Δresources (additional wheeling allocation amount).

[0099] Note that the objective function here is CO2 emissions, but OPEX can also be minimized by describing it in terms of retail supply charges, self-wheeling charges, or fuel unit prices instead of CO2 emissions.

[0100] First, in step S16a, the Δ resource calculation unit 222 of the base EMS 2-1 sets the wheeling allocation gain to a fixed value of 1 as a constraint condition, and calculates the vehicle operation plan, power supply and demand plan, and standard KPI (CO2 emissions) with the objective function being the minimization of CO2 emissions (forward calculation).

[0101] Next, in step S16b, the Δ resource calculation unit 222 replaces the objective function and constraint conditions in step S16a. That is, an upper limit of the improvement reference KPI is set as a constraint condition, and the objective function is set to minimize the wheeling distribution gain. The upper limit of the improvement reference KPI is a better value than the reference KPI, and when the reference KPI is the amount of CO2 emissions, it is a smaller value than the reference KPI.

[0102] Next, in step S16c, the Δ resource calculation unit 222 calculates the vehicle operation plan, the power supply and demand plan, the improvement criterion KPI, and the wheeling distribution gain using the constraint conditions and the objective function set in step S16b (reverse calculation). Here, if the improvement criterion KPI is not as the upper limit, the calculation is repeated.

[0103] Next, in step S16d, the Δ resource calculation unit 222 judges whether the improved KPI can be calculated in step S16c (whether there is a solution of the inverse calculation). If the improved KPI can be calculated in step S16c, the Δ resource calculation unit 222 proceeds to step S16e, and if the improved KPI cannot be calculated, the Δ resource calculation unit 222 proceeds to step S16g.

[0104] In step S16e, the Δ resource calculation unit 222 calculates the difference value ΔKPI (CO2 reduction amount) between the standard KPI calculated in step S16a and the improved KPI calculated in step S16c, and the wheeling distribution gain at that time. The Δ resource calculation unit 222 also calculates the Δ resource (wheeling distribution additional amount) by adding the calculated value of the wheeling distribution gain calculated in step S16c to the fixed value 1 of the wheeling distribution gain set in step S16a. However, the Δ resource (wheeling distribution additional amount) calculated here is the ratio of the resource after negotiation to the resource before negotiation.

[0105] Next, in step S16f, the Δ resource calculation unit 222 implements a resource addition proposal (transmits the Δ resource and ΔKPI to the multi-site integrated EMS 1, which is an allocation function).

[0106] On the other hand, in step S16g, the Δ resource calculation unit 222 postpones the resource addition proposal and does not execute it.

[0107] (Effects of the First Embodiment) In the above-described first embodiment, as long as the overall KPI is improved, the additional allocation of shared resources is prioritized for a base that has declared that its KPI will improve if shared resources are additionally allocated to that base. This allows the use plan for shared resources at multiple bases to be quickly drawn up on a first-come, first-served basis while optimizing the overall KPI.

[0108] (Modification of the first embodiment) Fig. 11 is an explanatory diagram of a modified example of the first embodiment. In the first embodiment, in the "multi-site fleet energy management" system, the "shared resource" is "surplus power" at a certain site, the "distribution function (integrated system)" is a multi-site integrated EMS1, the "subsystem" is a plurality of site EMS2, and the "KPI" is CO2 emissions. The "distribution function" distributes the "shared resource" to one of the "subsystems" so as to improve the overall KPI, which is the total value of the "KPIs" across all the "subsystems."

[0109] That is, in multi-site fleet energy management, the shared resource is the surplus electricity shared between sites through self-dispatch. The allocation function is the multi-site integrated EMS that draws up a dispatch allocation plan. The subsystem is the site EMS (including FMS) that draws up a power supply and demand plan and a vehicle operation plan for each site. The KPI is CO2 emissions or OPEX. If the addition of surplus electricity through self-dispatch (Δresource) increases the number of charging opportunities, it leads to an expansion of electrification coverage, and if the surplus electricity is a renewable energy source, CO2 emissions will clearly decrease (ΔKPI). In this case, even if the total electricity consumption of all sites increases (including an increase in retail supply), if the CO2 emissions per EV driving distance derived from retail supply (kg-CO2 / km) are less than the CO2 emissions per ICE driving distance, the CO2 reduction effect will be added.

[0110] However, the present invention is not limited to the above, and can also be applied to "multi-modal urban transportation" in which multiple types of transportation are linked. In this case, in multi-modal urban transportation, the shared resource is the waiting time allowed for each transportation means. The allocation function is a system of a public transportation manager that is responsible for ensuring convenience throughout the city, independent of each transportation operator. The subsystem is a system of an operator of a bus, a train, or the like. The KPI is the travel time of users. For example, if a main railway line is delayed and many users are forced to wait for the departure of a bus to which they are transferring, the convenience of users who only take the bus decreases, but the convenience of users who are transferring increases.

[0111] In other words, the "shared resource" is the "departure waiting time" of a certain transportation service, the "allocation function" is the system of the upper "public transportation manager," the "subsystems" are the systems of multiple bus and railway operators, and the "KPI" is the "passenger travel time." The "allocation function" then allocates the "shared resource" to one of the "subsystems" in order to improve the overall KPI, which is the sum of the "KPIs" across all the "subsystems."

[0112] This invention can also be applied to "mixed cargo and passenger transport" in transportation facilities where freight and passenger transport are mixed. In this case, in mixed cargo and passenger transport, the shared resource is the transport capacity of the transportation facility such as buses and trains. The allocation function is the transportation facility's operation system. The subsystems are the systems of passenger service providers (MaaS (Mobility as a Service) operators) that handle the movement of people and transport service providers (logistics operators) that handle the movement of goods. The KPI is the combined transport volume of people and goods. For example, if a transport service provider requests additional resources during peak train hours, the passenger boarding space will decrease, significantly impairing the KPI of passenger services.

[0113] On the other hand, during non-peak hours, even if the transport service provider requests additional resources, the passenger service KPIs will not be compromised, and the overall KPIs will improve in proportion to the improvement in the transport service KPIs.

[0114] In other words, the "shared resource" is the transportation capacity of the transportation facility, the "allocation function" is the transportation operation system, the "subsystems" are the systems of passenger service providers and logistics service providers, and the "KPI" is the "transportation volume of people and goods." The "allocation function" allocates the "shared resource" to one of the "subsystems" so as to improve the overall KPI, which is the sum of the "KPIs" across all the "subsystems."

[0115] [Embodiment 2] In the first embodiment, in response to a proposal for shared resource allocation from the allocation function, a subsystem at a certain site quickly submits a revised allocation proposal and has it approved by the subsystems at other sites, resulting in allocation of shared resources on a first-come, first-served basis.

[0116] In contrast, in the second embodiment, the allocation function calculates ΔKPI in each subsystem in response to a proposal for shared resource allocation from the allocation function, and when the ΣΔKPI satisfies the conditions in the allocation function, the allocation function has the subsystem of each site approve it. Hereinafter, the second embodiment will be described focusing on the differences from the first embodiment.

[0117] (Multiple resource management process according to the second embodiment (planning phase: resource allocation negotiation process) 12 is a flowchart showing an example of a resource management process (planning phase: resource allocation negotiation process) according to embodiment 2. In embodiment 2, the difference is that steps S19B, S20B, S23B, S24B, S25B, and S26B are executed instead of steps S19, S20, S23, S24, S25, and S26 of the resource management process (FIG. 3B), respectively.

[0118] In step S19B, the resource allocation plan unit 121 of the multi-site integrated EMS 1 recalculates the resource allocation plan, that is, the handover allocation plan, based on the resource addition proposal data D102 transmitted from the site EMS 2-1 in step S18.

[0119] In step S20B, the multi-site integrated EMS 1 transmits an approval / disapproval inquiry including the resource allocation plan recalculated in step S19B to the site EMSs 2-1 and 2-2.

[0120] In step S23B, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 determines the ΔKPI (ΔKPI calculated value) calculated in step S22 as the response to be sent to the multi-base integrated EMS 1. In step S24B, the ΔKPI evaluation and response unit 223 of the base EMS 2-1 determines the already calculated ΔKPI resource allocation plan of its own device as the response to be sent to the multi-base integrated EMS 1. This is because the resource allocation plan sent from the multi-base integrated EMS 1 in step S20B is based on the shared resource addition proposal proposed by its own device.

[0121] In step S25B, the resource usage planner 221 of the base EMS 2-2 transmits the answer determined in step S23B or S24B to the multi-base integrated EMS 1.

[0122] In step S26B, if the total ΣΔKPI of the ΔKPIs received from all the subsystems, that is, the base EMSs 2, is negative, the resource allocation plan unit 121 of the multi-site integrated EMS 1 adopts the resource allocation plan recalculated in step S19B. If the ΣΔKPI is negative, it means that the KPIs are improved throughout the resource management system S as a whole due to resource allocation.

[0123] (Aggregation of KPI responses according to the second embodiment) Fig. 13A is a diagram showing an example of the configuration of the ΣΔKPI (successful case) according to embodiment 2. Fig. 13B is a diagram showing an example of the configuration of the ΣΔKPI (unsuccessful case) according to embodiment 2.

[0124] In FIG. 13A, for the resource allocation plan with "ID" "Plan0001", the ΔKPI for base 1 (the proposer, base EMS2-1) is "-100", and the ΔKPI for base 2 (the decision maker, base EMS2-2) is "+80". In addition, the sum of the ΣΔKPI (CO2 emissions) across bases EMS2-1 and 2-2 is "-20". Since ΣΔKPI = "-20" is a negative value and the overall KPI has improved (total CO2 emissions have decreased), the adoption of the resource allocation plan with "ID" "Plan0001" is "established".

[0125] On the other hand, in FIG. 13B, for the resource allocation plan with "ID" "Plan0001", the ΔKPI for base 1 (the proposer, base EMS2-1) is "-100", and the ΔKPI for base 2 (the decision maker, base EMS2-2) is "+120". In addition, the sum of the ΣΔKPI (CO2 emissions) across bases EMS2-1 and 2-2 is "+20". Since ΣΔKPI = "+20" is a positive value and the overall KPI has worsened (total CO2 emissions have increased), the adoption of the resource allocation plan with "ID" "Plan0001" is "not established".

[0126] (Effects of the second embodiment) In the above-mentioned second embodiment, the multi-site integrated EMS has the base EMS, which is a subsystem, calculate the KPIs that are the basis for adopting the additional allocation of the shared resources, and determines whether to adopt the additional allocation of the shared resources based on the calculation results of the KPIs by each base EMS. Therefore, the multi-site integrated EMS can fairly formulate an additional allocation plan for the shared resources so as to optimize the overall KPI.

[0127] [Embodiment 3] In the third embodiment, the allocation function performs allocation by having each subsystem calculate a predetermined number of ΔKPIs in response to a proposal for shared resource allocation from the allocation function, and then searches for the combination of ΔKPIs that is the smallest in the allocation function and has each location approve it.

[0128] (ΔKPI / ΔResource Map According to the Third Embodiment) Fig. 14 is a diagram showing an example of a map of ΔKPI / Δresources according to the third embodiment. In this embodiment, there are three subsystems (three power receiving bases). A combination of the wheeling allocation amount and the CO2 emissions (ΔKPI·Δresources) at each base is calculated in advance in multiple patterns. Then, as shown in Fig. 14, ΔKPI / Δresources, which is the result of dividing ΔKPI by Δresources, is plotted on a graph with the wheeling allocation amount on the horizontal axis and the CO2 emissions on the vertical axis.

[0129] When the initial planning process receives the wheeling allocation time series data, each subsystem calculates multiple combinations of ΔKPI and Δresources and sends them to the allocation function. The allocation function selects the combination that minimizes CO2 emissions. In Figure 14, "●" indicates the initial allocation, and "●" and "○" connected by a solid line are combinations that minimize CO2 emissions without changing the total wheeling allocation amount (total Δresources is 0, ΔKPI is negative).

[0130] (ΔResource ΔKPI Dataset According to the Third Embodiment) Fig. 15 is a diagram showing an example of a dataset of Δresources·ΔKPI according to embodiment 3. The base EMS 2 of each base calculates combinations of the consignment allocation amount (Δresources) and the CO2 emission amount (ΔKPI) in multiple patterns for each base EMS 2 in advance, compiles them into the dataset shown in Fig. 15, and transmits them to the multi-base integrated EMS 1.

[0131] (Energy Management Process According to the Third Embodiment (Planning Phase: Initial Planning Process)) 16 is a flowchart showing an example of an energy management process (planning phase: initial planning process) according to embodiment 3. Embodiment 3 is different from embodiment 1 in that steps S141CB, S142C, S143C, and S144C are executed instead of step S14 between steps S13 to S15 of the energy management process (FIG. 3B).

[0132] In step S141C, the base EMSs 2-1 and 2-2 each create a ΔKPI / Δresource map. Next, in step S142C, the base EMSs 2-1 and 2-2 generate a Δresource·ΔKPI data set (FIG. 15) related to the ΔKPI / Δresource created in step S141C, and transmit it to the multi-base integrated EMS 1.

[0133] Next, in step S143C, the multi-site integrated EMS 1 determines a combination of Δ resources that minimizes ΣKPI (CO2 emissions). Next, in step S143C, the multi-site integrated EMS 1 notifies each site EMS 2 of the Δ resources to be allocated to each site related to the combination determined in step S143C.

[0134] (Effects of the Third Embodiment) In the above-mentioned third embodiment, the multi-site integrated EMS has each site EMS calculate the KPI and additional resources that are the basis for adopting the additional allocation of the shared resources, and calculates multiple combinations of ΔKPI and Δresources for each site EMS.Then, the multi-site integrated EMS selects, for each site EMS, a combination that optimizes the overall KPI from among the combinations of ΔKPI and Δresources for each site EMS.Therefore, it is possible to create an additional allocation plan that optimizes the overall KPI while fairly allocating additional shared resources to each site.

[0135] Although the embodiments of the present disclosure have been described above in detail, the present disclosure is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit of the present disclosure. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present disclosure is not necessarily limited to those having all of the configurations described. In addition, it is possible to add, delete, or replace part of the configuration of the above-described embodiments with other configurations.

[0136] Furthermore, the above-mentioned configurations, functional units, processing units, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. The above-mentioned configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information such as the program, table, file, etc. that realizes each function can be stored in a memory, a storage device such as an HDD or SSD, or a recording medium such as an IC card, an SD card, or a DVD.

[0137] In addition, in each of the above figures, the control lines and information lines are shown as those considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the actual implementation. For example, it may be considered that almost all the components are actually connected to each other.

[0138] The above-mentioned arrangement of functions and data of the multi-site integrated EMS 1 and the site EMSs 2, 2-1, and 2-2 is merely an example. The arrangement of functions and data and the arrangement and distribution of the functions and data can be changed to an optimal form in terms of hardware and software performance, processing efficiency, communication efficiency, etc. [Explanation of symbols]

[0139] S: resource management system, 1: multi-site integrated EMS, 2, 2-1, 2-2: site EMS, 12, 22: computing device, 13, 23: storage device.

Claims

1. A resource management system that includes a plurality of subsystems and calculates a resource allocation plan for allocating resources to the plurality of subsystems, The resource management system includes a processor and a memory. The processor of the resource management system determining an initial resource allocation plan for implementing the initial allocation of resources to the plurality of subsystems; Calculating a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is performed based on the initial resource allocation plan; By solving an optimization problem in which the change amount of the KPI is used as a constraint condition and the additional allocation amount of the resource is used as an objective function for each subsystem, the additional allocation amount in the subsystem that improves the KPI compared to the initial resource allocation plan when the resource is reallocated based on the additional allocation amount is calculated; Calculating a resource reallocation plan for reallocating the resources to the plurality of subsystems based on the additional allocation amount, and an expected value of the KPI that is expected to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; Calculating the calculated value of the KPI that each of the plurality of subsystems will actually achieve when the resources are reallocated based on the resource reallocation plan; Decide whether to accept the resource reallocation plan for each subsystem by comparing the calculated value of the KPI with the expected value of the KPI and rejecting the acceptance of the resource reallocation plan if the calculated value of the KPI deteriorates, and accepting the acceptance if the calculated value of the KPI does not deteriorate; Deciding whether to adopt the resource reallocation plan based on the acceptability of each of the plurality of subsystems. A resource management system comprising:

2. 2. The resource management system according to claim 1, The processor of the resource management system The KPI obtained from an optimization problem in which a constraint based on the additional allocation amount and an objective function based on the KPI are set is calculated as a reference KPI; The KPI obtained from an optimization problem in which a constraint condition based on the KPI and an objective function based on the additional allocation amount are set is calculated as an improved KPI; When the improved KPI is calculable, the additional allocation amount is calculated based on the difference between the standard KPI and the improved KPI. A resource management system comprising:

3. 2. The resource management system according to claim 1, each of the plurality of subsystems is an EMS (Energy Management System) that calculates, for each base of vehicles including electric vehicles (EVs) equipped with a distributed power source and an EV charger, an electric power supply and demand plan and a vehicle operation plan that are resource utilization plans based on the initial resource allocation plan and the resource reallocation plan; The resource management system is a fleet energy management system including an integrated EMS that integrates a plurality of the EMSs, the resource is surplus power per unit time totaled across all of the bases, The KPI is the amount of CO2 emissions associated with the operation of the vehicle, The integrated EMS has a processor and a memory; The processor of the integrated EMS For each unit time, Calculating the initial resource allocation plan, the resource reallocation plan, and an assumed value of the KPI; determining whether to adopt the resource reallocation plan; The processor of each of the plurality of EMSs For each unit time, Calculating the KPI, the additional allocation amount, and the calculated value of the KPI; determining said acceptance of said resource reallocation plan; A resource management system comprising:

4. 4. The resource management system according to claim 3, The processor of each of the plurality of EMSs For each unit time, Calculating the CO2 emission amount obtained from an optimization problem in which a constraint condition that fixes the additional allocation amount of the surplus electricity to 1 and an objective function that minimizes the CO2 emission amount are set as a reference KPI; Calculating the CO2 emission amount obtained from an optimization problem in which a constraint condition for setting an upper limit value for the CO2 emission amount and an objective function for minimizing the additional allocation amount are set as an improvement KPI; When the improved KPI is calculable, the additional allocation amount is calculated based on a difference between the improved KPI and the standard KPI. A resource management system comprising:

5. 5. The resource management system according to claim 4, The processor of the or each of the integrated EMS Displaying a change in the KPI associated with the reallocation of resources based on the additional allocation amount on a display screen A resource management system comprising:

6. 2. The resource management system according to claim 1, The resource management system includes an integrated system having a processor and a memory; Each of the plurality of subsystems includes a processor and a memory; The processor of each of the plurality of subsystems comprises: Calculating the KPI, the additional allocation amount, the estimated value of the KPI, the calculated value of the KPI, and a difference between the estimated value of the KPI and the calculated value of the KPI for each subsystem; The processor of the integrated system includes: Instead of determining the acceptability for each of the subsystems and determining whether to adopt the resource reallocation plan based on the acceptability for each of the plurality of subsystems, The resource reallocation plan is adopted if the total value of the calculated KPIs for all of the plurality of subsystems is improved by comparing the total value of the estimated KPIs for all of the plurality of subsystems, and is not adopted if the total value of the calculated KPIs for all of the plurality of subsystems is improved. A resource management system comprising:

7. 2. The resource management system according to claim 1, The resource management system includes an integrated system having a processor and a memory; Each of the plurality of subsystems includes a processor and a memory; The processor of each of the plurality of subsystems comprises: Calculating the KPI, the additional allocation amount, the estimated value of the KPI, the calculated value of the KPI, and a difference between the estimated value of the KPI and the calculated value of the KPI for each subsystem; Instead of determining the acceptability for each of the subsystems, a plurality of patterns of combinations of the additional allocation amount and the difference value are generated; The processor of the integrated system includes: Instead of determining whether to adopt the resource reallocation plan based on the acceptability of each of the subsystems, determining a combination that provides the best total value of the difference values ​​for all of the plurality of subsystems from among combinations of the additional allocation amounts and the difference values ​​for all of the plurality of subsystems; notifying each of the subsystems of the additional allocation amount for each of the subsystems related to the determined combination; A resource management system comprising:

8. An integrated resource management device that calculates a resource allocation plan for allocating resources to a plurality of subsystems, comprising: The integrated resource management device includes a processor and a memory. The processor of the integrated resource management device determining an initial resource allocation plan for implementing the initial allocation of resources to the plurality of subsystems; Calculating a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is performed based on the initial resource allocation plan; calculate a resource reallocation plan for reallocating resources to the multiple subsystems based on an additional allocation amount in the subsystem that improves the KPI compared to the initial resource allocation plan when the resources are reallocated based on the additional allocation amount, the additional allocation amount being calculated by solving an optimization problem for each subsystem with an amount of change in the KPI as a constraint condition and an amount of additional allocation of the resources as an objective function; and calculate an expected value of the KPI that is expected to be achieved by each of the multiple subsystems when the resources are reallocated based on the resource reallocation plan; A calculation value of the KPI that each of the plurality of subsystems actually achieves when the resources are reallocated based on the resource reallocation plan, which is determined for each subsystem, is compared with an assumed value of the KPI, and if the calculated value deteriorates, the acceptance of the resource reallocation plan is rejected, and if the calculated value does not deteriorate, the acceptance is accepted. Based on the acceptability, the adoption of the resource reallocation plan is decided.

1. An integrated resource management device comprising:

9. A resource management method executed by a resource management system including a plurality of subsystems and calculating a resource allocation plan for allocating resources to the plurality of subsystems, comprising: The resource management system includes a processor and a memory. a processor of the resource management system, calculating an initial resource allocation plan for implementing the initial allocation of resources to the plurality of subsystems; calculating a key performance indicator (KPI) that each of the plurality of subsystems will achieve when the initial allocation is performed based on the initial resource allocation plan; a step of calculating an additional allocation amount in the subsystem that improves the KPI compared to the initial resource allocation plan when the resources are reallocated based on the additional allocation amount by solving an optimization problem in which the amount of change in the KPI is used as a constraint condition and the additional allocation amount of the resources is used as an objective function for each of the subsystems; calculating a resource reallocation plan for reallocating the resources to the plurality of subsystems based on the additional allocation amount, and an expected value of the KPI that is expected to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; calculating a calculated value of the KPI that each of the plurality of subsystems will actually achieve when the resources are reallocated based on the resource reallocation plan; A step of deciding whether to accept the resource reallocation plan for each of the subsystems by comparing the calculated value of the KPI with an expected value of the KPI and refusing to accept the resource reallocation plan if the calculated value of the KPI deteriorates, and accepting the plan if the calculated value of the KPI does not deteriorate; determining whether to adopt the resource reallocation plan based on the acceptability of each of the plurality of subsystems; 13. A resource management method comprising:

10. 10. A resource management method according to claim 9, comprising: The resource management system includes an integrated system having a processor and a memory; Each of the plurality of subsystems includes a processor and a memory; a processor of each of the plurality of subsystems, Calculating the KPI, the additional allocation amount, the estimated value of the KPI, the calculated value of the KPI, and a difference between the estimated value of the KPI and the calculated value of the KPI for each subsystem; a processor of the integrated system, Instead of determining the acceptability for each of the subsystems and determining whether to adopt the resource reallocation plan based on the acceptability for each of the plurality of subsystems, A step of deciding to adopt the resource reallocation plan when the total value of the calculated KPIs for all of the plurality of subsystems improves by comparing the total value of the calculated KPIs for all of the plurality of subsystems with the total value of the estimated KPIs for all of the plurality of subsystems, and deciding not to adopt the resource reallocation plan when the total value of the calculated KPIs for all of the plurality of subsystems improves, and deciding not to adopt the resource reallocation plan when the total value of the calculated KPIs for all of the plurality of subsystems does not improve.

13. A resource management method comprising:

11. 10. A resource management method according to claim 9, comprising: The resource management system includes an integrated system having a processor and a memory; Each of the plurality of subsystems includes a processor and a memory; a processor of each of the plurality of subsystems, Calculating the KPI, the additional allocation amount, the estimated value of the KPI, the calculated value of the KPI, and a difference between the estimated value of the KPI and the calculated value of the KPI for each subsystem; a step of generating a combination of a plurality of patterns of the additional allocation amount and the difference value instead of the step of determining whether or not the additional allocation amount is acceptable for each subsystem; a processor of the integrated system, Instead of the step of determining whether to adopt the resource reallocation plan based on the acceptability of each of the subsystems, determining a combination that provides the best total value of the difference values ​​for all of the plurality of subsystems from among combinations of the additional allocation amounts and the difference values ​​for all of the plurality of subsystems; notifying each of the subsystems of the additional allocation amount for each of the subsystems related to the determined combination; 13. A resource management method comprising:

12. A resource management method executed by an integrated resource management device that calculates a resource allocation plan for allocating resources to a plurality of subsystems, comprising: The integrated resource management device includes a processor and a memory. A processor of the integrated resource management device calculating an initial resource allocation plan for implementing the initial allocation of resources to the plurality of subsystems; calculating a key performance indicator (KPI) that each of the plurality of subsystems will achieve when the initial allocation is performed based on the initial resource allocation plan; calculating a resource reallocation plan for reallocating resources to the plurality of subsystems based on an additional allocation amount in the subsystem that improves the KPI compared to the initial resource allocation plan when the resources are reallocated based on the additional allocation amount, the additional allocation amount being calculated by solving an optimization problem for each subsystem with an amount of change in the KPI as a constraint condition and an amount of additional allocation of the resources as an objective function, and an expected value of the KPI that is expected to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; a step of deciding whether or not to adopt the resource reallocation plan based on the acceptability of rejecting the acceptance of the resource reallocation plan if the calculated value of the KPI actually achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan, which is determined for each subsystem, deteriorates when compared with the assumed value of the KPI, and accepting the acceptance if the KPI does not deteriorate; 13. A resource management method comprising:

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